Let's say I have a stock that I own and the value of that stock over 4 days. I also know if the stock on that day falls into one of 2 categories. On each day I want to make a feature out of the percentage difference in the price of that stock from yesterday.
So for the sake of this example we have 4 data points:
S1 - Jan 1, 2019 - -5% - 1
S1 - Jan 2, 2019 - 4% - 0
S1 - Jan 3, 2019 - 2% - 1
S1 - Jan 4, 2019 - 4% - 0
I want to use a time split to train my model, so I will begin by only training on the the first 2 days, validating on the 3rd, and testing on the 4th. Is it correct to include both the 1st and 2nd as separate inputs in my training set?
So far that is what I have done, and it has given me results that are a little too good to be true